| 101. |
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| 102. |
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| 103. |
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| 104. |
- Kilpelainen, TO, et al.
(författare)
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Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity
- 2019
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Ingår i: Nature communications. - London : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 376-
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Tidskriftsartikel (refereegranskat)abstract
- Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.
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| 105. |
- Kousathanas, A, et al.
(författare)
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Whole-genome sequencing reveals host factors underlying critical COVID-19
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 607:7917, s. 97-
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Tidskriftsartikel (refereegranskat)abstract
- Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.
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| 106. |
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| 107. |
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| 108. |
- Law, PJ, et al.
(författare)
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Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia
- 2017
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8, s. 14175-
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Tidskriftsartikel (refereegranskat)abstract
- Several chronic lymphocytic leukaemia (CLL) susceptibility loci have been reported; however, much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1,000 Genomes and UK10K data, totalling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P=5.04 × 10−13), 1q42.13 (rs41271473, P=1.06 × 10−10), 4q24 (rs71597109, P=1.37 × 10−10), 4q35.1 (rs57214277, P=3.69 × 10−8), 6p21.31 (rs3800461, P=1.97 × 10−8), 11q23.2 (rs61904987, P=2.64 × 10−11), 18q21.1 (rs1036935, P=3.27 × 10−8), 19p13.3 (rs7254272, P=4.67 × 10−8) and 22q13.33 (rs140522, P=2.70 × 10−9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for the key determinants of B-cell development and immune response.
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| 109. |
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| 110. |
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